Nature Machine Intelligence
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Principled approaches for extending neural architectures to function spaces for operator learning
Principled approaches for extending neural architectures to function spaces for operator learning Nature
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Reshaping biomolecular structure prediction through strategic conformational exploration with HelixFold-S1
Nature Machine Intelligence, Published online: 02 July 2026; doi:10.1038/s42256-026-01264-2 Liu and colleagues introduce HelixFold-S1, a guided sampling strategy for biomolecular complex structure prediction that targets high-probability interaction regions. The method achieves h…
Read full story →Empowering biomedical evidence exploration and synthesis with deep knowledge graph research
Nature Machine Intelligence, Published online: 02 July 2026; doi:10.1038/s42256-026-01266-0 Wang et al. develop DeepEvidence, a biomedical deep research agent for exploring and synthesizing evidence across various knowledge sources to support drug discovery, clinical trials and e…
Read full story →An agentic artificially intelligent X-ray scientist
Nature Machine Intelligence, Published online: 01 July 2026; doi:10.1038/s42256-026-01261-5 Chen et al. demonstrate an AI X-ray scientist that autonomously aligns single crystals at a real synchrotron beamline, showing how large language models can enable adaptive closed-loop exp…
Read full story →Bridging three-dimensional molecular structures and artificial intelligence with a conformation description language
Nature Machine Intelligence, Published online: 11 June 2026; doi:10.1038/s42256-026-01250-8 Xiong et al. introduce ConfSeq, a molecular conformation description language that enables language models to perform three-dimensional molecular modelling tasks, including conformer predi…
Read full story →From virtual experiments to biomedical insight with synthetic data
Nature Machine Intelligence, Published online: 11 June 2026; doi:10.1038/s42256-026-01244-6 Synthetic datasets are becoming crucial for the development of biomedical machine learning models. Victoriano et al. discuss the persistent simulation-to-reality gap that limits how well s…
Read full story →Towards AI-augmented decision making in psychiatry
Nature Machine Intelligence, Published online: 12 June 2026; doi:10.1038/s42256-026-01256-2 Psychiatric disorders are heterogeneous, and care depends on interpreting unstructured longitudinal narratives, creating variability that hinders standardization. A study now shows that a…
Read full story →Algorithm–hardware co-design of neuromorphic networks with dual memory pathways
Nature Machine Intelligence, Published online: 16 June 2026; doi:10.1038/s42256-026-01255-3 Pengfei Sun et al. develop a spiking neural network with a dual memory pathway, co-designed with a custom neuromorphic chip. The approach delivers over 4× throughput and 5x energy efficien…
Read full story →Autonomous navigation of intelligent microrobotic swarms in unknown environments
Nature Machine Intelligence, Published online: 22 June 2026; doi:10.1038/s42256-026-01252-6 An, Luo, Zhang and colleagues present Turbo, a transformer-based reinforcement learning framework that enables simulation-to-real transfer for autonomous navigation and obstacle avoidance…
Read full story →A dexterous soft hand exoskeleton restores intentional grasping in individuals with severe hand impairment
Nature Machine Intelligence, Published online: 23 June 2026; doi:10.1038/s42256-026-01263-3 Nassour, Berberich and colleagues present a soft robotic hand exoskeleton that restores grasping ability in individuals with severe hand paralysis, enabling meaningful tasks such as feedin…
Read full story →Solutions, challenges and rising tensions in AI and mathematics
Nature Machine Intelligence, Published online: 23 June 2026; doi:10.1038/s42256-026-01269-x Recent breakthroughs in mathematical research show that AI is transforming the field at a remarkable pace. In an open letter published this month, an international group of mathematicians…
Read full story →Data-driven surrogates of rational design enable antimicrobial peptide optimization
Nature Machine Intelligence, Published online: 25 June 2026; doi:10.1038/s42256-026-01258-0 Rising pathogen drug resistance makes next-generation antimicrobial peptides a global priority. Generative AI accelerates discovery by rapidly proposing new peptides with high therapeutic…
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